# MusicBrainz Scraper — Artists, Releases & Recordings (`logiover/musicbrainz-scraper`) Actor Scrape MusicBrainz by artist, release, recording, or label. Extract id, name, type, country, tags, score, life-span, and area. No API key, no login. Bulk pagination up to thousands of results. - **URL**: https://apify.com/logiover/musicbrainz-scraper.md - **Developed by:** [Logiover](https://apify.com/logiover) (community) - **Categories:** Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## MusicBrainz Scraper — Artists, Releases, Recordings & Labels Extract open music metadata from MusicBrainz with no API key required — search artists, releases, recordings, and labels at scale, with full pagination and structured output. ### What does MusicBrainz Scraper do? MusicBrainz Scraper connects directly to the official MusicBrainz JSON Web Service (`https://musicbrainz.org/ws/2/`) — a fully open, key-free music metadata API. You choose a mode (artist, release, recording, or label), provide a search query, and the actor paginates through results in batches of up to 100, respecting MusicBrainz's ~1 req/sec rate limit. Each result is normalized into a clean flat object: ID, name/title, type, country, area, begin/end dates, disambiguation, relevance score, and tags. The actor handles transient errors with automatic retries and exponential back-off. A single run can retrieve hundreds to thousands of entries — ideal for bulk music research, catalog enrichment, or analytics pipelines. No credentials, no login, no browser — pure API. ### Who is it for? - **Music researchers and academics** who need structured discography or artist data in bulk for analysis. - **Music streaming and playlist apps** that need to enrich track or artist metadata from a trusted open registry. - **Data journalists** covering music industry trends, genre evolution, or country-level artist distributions. - **Record label teams** auditing catalog coverage and cross-referencing MusicBrainz IDs with internal databases. - **Developers and data engineers** building music knowledge graphs, recommendation systems, or tagging pipelines. ### Use cases - Build a complete discography database for a genre by searching releases with genre-tagged queries. - Cross-reference your internal artist catalog with MusicBrainz IDs for deduplication and canonical linking. - Extract all labels registered to a specific country for market research or licensing analysis. - Collect artist life-span and area data to map music scenes geographically over time. - Automate metadata enrichment for a music library by searching recordings and pulling canonical titles and dates. ### Why use MusicBrainz Scraper? - **Completely keyless** — no API key, no account, no login required from you or your users. - **12 structured output fields** — id, name, type, country, score, area, beginDate, endDate, disambiguation, tags, mode, url. - **Bulk pagination** — retrieve up to 10,000 results per run via automatic offset pagination. - **Four entity modes** — artists, releases, recordings, and labels all in one actor. - **Export anywhere** — download results as CSV, JSON, Excel, or JSONL directly from Apify. - **Pay-per-result pricing** — you only pay for the data rows you actually retrieve. ### What data can you extract? The actor extracts the following fields for every result: | Field | Type | Description | |---|---|---| | `id` | string | MusicBrainz unique identifier (MBID) | | `name` | string | Artist name, release title, recording title, or label name | | `type` | string | Entity type (e.g. "Person", "Group", "Album", "Single") | | `country` | string | ISO country code (e.g. "GB", "US", "JP") | | `disambiguation` | string | Parenthetical note to distinguish entities with the same name | | `score` | string | Relevance match score (0–100) returned by MusicBrainz search | | `area` | string | Geographic area associated with the entity | | `beginDate` | string | Formation/release/founded date (YYYY or YYYY-MM-DD) | | `endDate` | string | Dissolution/ended date if applicable | | `tags` | string | Comma-separated genre/style tags from the community | | `mode` | string | Which search mode was used (artistSearch, releaseSearch, etc.) | | `url` | string | Direct MusicBrainz URL for the entity | **Example JSON output (artist):** ```json { "id": "a74b1b7f-71a5-4011-9441-d0b5e4122711", "name": "Radiohead", "type": "Group", "country": "GB", "disambiguation": "", "score": "100", "area": "United Kingdom", "beginDate": "1985", "endDate": null, "tags": "rock, alternative rock, art rock, post-rock, electronic", "mode": "artistSearch", "url": "https://musicbrainz.org/artist/a74b1b7f-71a5-4011-9441-d0b5e4122711" } ```` ### How to use #### Option A — Search by artist name 1. Open the actor in Apify Console. 2. Set **mode** to `artistSearch`. 3. Enter the artist name in **query** (e.g. "Radiohead", "Nina Simone", "Daft Punk"). 4. Set **maxResults** to however many you need (default 100, max 10000). 5. Click **Start** and download results as JSON or CSV. **Input JSON:** ```json { "mode": "artistSearch", "query": "Radiohead", "maxResults": 100 } ``` #### Option B — Search releases, recordings, or labels 1. Set **mode** to one of: `releaseSearch`, `recordingSearch`, or `labelSearch`. 2. Enter a descriptive query — can include album name, artist clause, year, etc. 3. MusicBrainz supports Lucene-style field queries: e.g. `artist:Radiohead AND type:album`. 4. Increase **maxResults** for bulk extraction. **Input JSON:** ```json { "mode": "releaseSearch", "query": "OK Computer", "maxResults": 200 } ``` ### Input parameters | Parameter | Type | Default | Description | |---|---|---|---| | `mode` | string | `artistSearch` | Entity to search: `artistSearch`, `releaseSearch`, `recordingSearch`, `labelSearch` | | `query` | string | — | Free-text or Lucene-style search query | | `maxResults` | integer | 100 | Max rows to collect (1–10000) | | `proxyConfiguration` | object | — | Optional Apify proxy settings | **Full input JSON:** ```json { "mode": "artistSearch", "query": "Beatles", "maxResults": 500, "proxyConfiguration": { "useApifyProxy": false } } ``` ### Output example ```json { "id": "b10bbbfc-cf9e-42e0-be17-e2c3e1d2600d", "name": "The Beatles", "type": "Group", "country": "GB", "disambiguation": "", "score": "100", "area": "United Kingdom", "beginDate": "1960", "endDate": "1970", "tags": "rock, pop, british invasion, classic rock, merseybeat", "mode": "artistSearch", "url": "https://musicbrainz.org/artist/b10bbbfc-cf9e-42e0-be17-e2c3e1d2600d" } ``` ### Tips for best results - **Use Lucene field syntax** for precision: `artist:Radiohead AND type:album` in releaseSearch gives cleaner results than a plain title query. - **Score field** indicates relevance — filter downstream for `score >= 80` to keep high-confidence matches. - **Disambiguation field** helps when multiple entities share a name — always inspect it when deduplicating. - **Rate limit is respected** — the actor inserts a 1.1 s delay between requests as required by MusicBrainz ToS; don't try to bypass it. - **Pagination is automatic** — just set a high `maxResults` and the actor handles all offsets. - **Tags are community-sourced** — great for genre analysis but may be incomplete for obscure artists. - **Country codes** follow ISO 3166-1 alpha-2 (e.g. "US", "JP", "DE"); filter in spreadsheet tools after download. - **beginDate/endDate formats vary** — some entries have full YYYY-MM-DD, others only YYYY or YYYY-MM. - **For label research**, combine country filter in your query: `label:EMI AND country:GB`. - **MBID (id field)** is stable and globally unique — use it as your canonical music entity key in databases. ### Integrations - **Google Sheets** — Use Apify's Google Sheets integration to push results directly to a spreadsheet for team collaboration. - **Slack** — Set up a webhook to notify your channel when a scheduled MusicBrainz run completes. - **Zapier / Make** — Connect actor runs to thousands of apps: save to Airtable, send rows to a CRM, or trigger downstream processing. - **Webhooks** — Configure Apify webhooks to POST the dataset URL to your server when the run finishes. - **Scheduler** — Schedule weekly runs to keep your music metadata dataset fresh with the latest MusicBrainz updates. ### API usage **cURL:** ```bash curl -X POST \ "https://api.apify.com/v2/acts/logiover~musicbrainz-scraper/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{"mode":"artistSearch","query":"Radiohead","maxResults":100}' ``` **Node.js (Apify client):** ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_TOKEN' }); const run = await client.actor('logiover~musicbrainz-scraper').call({ mode: 'artistSearch', query: 'Radiohead', maxResults: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` **Python:** ```python from apify_client import ApifyClient client = ApifyClient("YOUR_TOKEN") run = client.actor("logiover~musicbrainz-scraper").call(run_input={ "mode": "artistSearch", "query": "Radiohead", "maxResults": 100, }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` ### Use with AI agents (MCP) MusicBrainz Scraper is available via the Apify MCP server, making it instantly usable from Claude, ChatGPT, and any MCP-compatible agent. Just connect the Apify MCP server and prompt your agent: *"Search MusicBrainz for all releases by Portishead and give me their dates and countries"* — the agent will trigger a run, wait for results, and summarize them inline. ### FAQ #### Does this require an API key or account? No. MusicBrainz's JSON Web Service is publicly accessible without registration. You only need an Apify account to run the actor. #### How much data can I extract per run? Up to 10,000 results per run. MusicBrainz returns up to 100 per page; the actor paginates automatically via offset until `maxResults` is reached or the result set is exhausted. #### Why is there a 1-second delay between requests? MusicBrainz's usage policy requires clients to send at most 1 request per second. The actor enforces a 1.1 s delay to stay compliant and avoid being rate-limited or blocked. #### What happens if my query returns zero results? The actor logs a warning and exits cleanly with an empty dataset. Check your query spelling; MusicBrainz search is fuzzy but typos still reduce results significantly. #### Why are some fields null? MusicBrainz is community-curated — many entities lack complete metadata. Fields like `endDate`, `country`, and `tags` are frequently null for less well-documented artists or releases. #### Can I export results to Excel or CSV? Yes. From the Apify dataset view, click **Export** and choose CSV, Excel, JSON, or JSONL. Google Sheets export is also available via the Apify integration. #### How fast does it run? Because of the 1 req/sec rate limit, 100 results take about 1 minute, 1,000 results take about 10 minutes. Plan accordingly for large extractions. #### Is this legal to use? Yes. MusicBrainz data is published under Creative Commons licenses (CC0 for the core data). The actor respects the rate limit and sends a descriptive User-Agent header as required by MusicBrainz policy. #### What is the score field? MusicBrainz search returns a relevance score (0–100) indicating how closely each result matches your query. A score of 100 means an exact match; lower scores indicate partial matches. #### How often is MusicBrainz data updated? MusicBrainz is continuously edited by its community. The API reflects the live database in near-real-time. Schedule weekly runs to keep your local data current. #### Can I search for a specific artist's releases? Yes — use `releaseSearch` with a Lucene artist clause: `query: "artist:Radiohead AND type:album"`. This targets releases credited to that artist. #### Are there related scrapers I should know about? Absolutely. You might also find these logiover actors useful: - **Discogs Scraper** — vinyl marketplace, release editions, and user collections. - **Last.fm Scraper** — scrobble counts, listener stats, and tag-based discovery. - **Spotify Unofficial API** — track features, playlist data, and artist popularity scores. - **IMDb Scraper** — for soundtracks and film-music metadata cross-referencing. ### Is it legal? MusicBrainz data is released under Creative Commons CC0 (public domain dedication) for factual data and CC BY-NC-SA for Wikipedia-derived text. The actor accesses only the public JSON API with a compliant User-Agent and rate limit. No authentication is bypassed, no personal data is collected. Always review MusicBrainz's [Terms of Service](https://metabrainz.org/terms) for your specific use case, especially for commercial redistribution of large dataset dumps. # Actor input Schema ## `mode` (type: `string`): Which entity type to search. ## `query` (type: `string`): Free-text search query (e.g. artist name, album title, song name, label name). Use broad terms like 'rock', 'jazz', 'pop' for large result sets. Leave EMPTY to browse a broad recent listing of the selected entity. ## `maxResults` (type: `integer`): Maximum number of results to return. MusicBrainz returns up to 100 per page; pagination fetches more. Set to 500+ for bulk exports. ## `proxyConfiguration` (type: `object`): Optional proxy settings. MusicBrainz is an open API; automatic Apify Proxy is recommended. ## Actor input object example ```json { "mode": "releaseSearch", "query": "rock", "maxResults": 500, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): All records extracted by this run. Open the Dataset tab to browse, filter, and export as CSV, JSON, or Excel. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "query": "rock", "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("logiover/musicbrainz-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "query": "rock", "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("logiover/musicbrainz-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "query": "rock", "proxyConfiguration": { "useApifyProxy": true } }' | apify call logiover/musicbrainz-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=logiover/musicbrainz-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MusicBrainz Scraper — Artists, Releases & Recordings", "description": "Scrape MusicBrainz by artist, release, recording, or label. Extract id, name, type, country, tags, score, life-span, and area. No API key, no login. Bulk pagination up to thousands of results.", "version": "1.0", "x-build-id": "cvFOT3gvf1Me5Fqae" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/logiover~musicbrainz-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-logiover-musicbrainz-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/logiover~musicbrainz-scraper/runs": { "post": { "operationId": "runs-sync-logiover-musicbrainz-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/logiover~musicbrainz-scraper/run-sync": { "post": { "operationId": "run-sync-logiover-musicbrainz-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "mode": { "title": "Search Mode", "enum": [ "artistSearch", "releaseSearch", "recordingSearch", "labelSearch" ], "type": "string", "description": "Which entity type to search.", "default": "releaseSearch" }, "query": { "title": "Search Query", "type": "string", "description": "Free-text search query (e.g. artist name, album title, song name, label name). Use broad terms like 'rock', 'jazz', 'pop' for large result sets. Leave EMPTY to browse a broad recent listing of the selected entity." }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of results to return. MusicBrainz returns up to 100 per page; pagination fetches more. Set to 500+ for bulk exports.", "default": 500 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Optional proxy settings. MusicBrainz is an open API; automatic Apify Proxy is recommended." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```